Triple
T26815975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lantau Peak |
E675121
|
entity |
| Predicate | rankingByElevationInHongKong |
P27607
|
FINISHED |
| Object | second highest peak |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: second highest peak | Statement: [Lantau Peak, rankingByElevationInHongKong, second highest peak]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingByElevationInHongKong Context triple: [Lantau Peak, rankingByElevationInHongKong, second highest peak]
-
A.
rankInCityByHeight
chosen
Indicates the relative ordering of entities within a specific city based on their height, such as which is tallest, second tallest, and so on.
-
B.
precededByTallestInHongKong
Indicates that one entity comes immediately before the tallest entity in Hong Kong in a specified sequence or ordering.
-
C.
succeededByTallestInHongKong
Indicates that one entity is succeeded or replaced by another entity that is the tallest in Hong Kong.
-
D.
rankAmongWorldsHighestMountains
Indicates that the subject mountain is among the tallest mountains in the world in terms of elevation.
-
E.
mountainHeight
Indicates the vertical elevation or height of a mountain, typically measured from sea level.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69eee9b6b28481909332f83eb17e5170 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 27, 2026, 4:52 a.m.